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| 摘要: |
| 讨论了如何应用人工神经网络（ANN）的方法预测混凝土抗压强度，详细论述了采用BP算法建立混凝土抗压强度神经网络模型的过程，以及在活化剂作用下高掺量粉煤灰混凝土的强度效应，仿真结果表明，通过学习，BP网络可成功地建立非线性的强度模型，预测强度可达到较高精度。 |
| 关键词: 人工神经网络 混凝土 BP算法 |
| DOI： |
| 分类号:TU528.01 |
| 基金项目: |
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| Application of Artificial Neural Networks for Analyzing Concrete Strength |
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HAN Min XI Jian hui WANG Li jiu WANG Jin cheng
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| Abstract: |
| Neural networks was established to predict the compressive strength of concrete at different age and special emphasis was put on the strength efficiency of high fly ash content concrete. In order to establish neural networks, two important features were defined. One was connection topology of networks, and the other was the learning rule of networks. From the simulation results, conclusion comes as: (1) The compressive strengh of concrete with high content of fly ash (HFCC) can be predicted successfully by use of the model of neural networks. (2) HFCC can be realized with effective chemical admixture. It will lead to obvious reduction of cement proportion and be good for environment protection. |
| Key words: artificial neural network,concrete, BP algorithm |
